Concepto de red social y su clasificación

A. Back on the research question

Our first research question was about the strategies developed by farmers linked with their environment and on how they organize their management around the diversification of the animal enterprises. After analysing farms structures and environment, we were able to describe each farm with their own specificities. Those specificities are useful to explain the context in where farm strategies are tested and developed. Indeed, the farm structure, which can be more or less constraining, revealed farmer’s strategic adaptations to make his system viable. Then, we analysed farmer’s practices which helped us to understand farmers choices and strategies behind these practices. Farmers practices have been classified regarding if they follow agroecological principles or not. It helped us to determine if the farmers tend to “green up” their practices or if they follow other principles/goals. We found that a large majority of the farms adopted practices deeply linked to their resources and environment. We observed different strategies in order to adapt farming practices with their social, economic and ecological environment. Each practice is a result of a specific farming strategy.

For a better comprehension of farms history and it adaptation capacity, we drew and analysed farms trajectories. With those three individual analytic element, we are able to establish farms profiles described by their structural characteristic, their practices and their evolution in time. The individual analysis allows us to approach strategies and management modalities for each farm, but it is not enough to understand if there is a common model or strategy regarding animal diversity. The transversal analysis seems relevant to draw functioning models linked with the animal mixing, corresponding to the third question. Each farm shares the fact of having two or more animal species and we wanted to understand if common strategies does exist. The typology allows us to distinguish three different strategies. This typology seems useful to determine mixed farms models. The next step was to assess these models with the “La Grange” method. This final step in the analysis allows to link farmers strategies with their contribution to the territory dynamic. The final assessment reveals that each model contribute to the agroecological development of its territory but with different levels and scales. Each model have a unique contribution to its environment and the three models can coexist in the same territory. The transversal analysis allows us to answer to the third question about MLS models and their contribution to the territory.

The second research question “which performances, sustainability and resilience?” is the less addressed question. We did not make a sustainability and performances assessment such as IDEA because of the disparities in the data. Yet, we were able to approach it with the agroecological principles, the concept of autonomy and some relevant indicators (social networks, subsidies dependencies). The concept of resilience is wide and hard to assess regarding our farms. The study of farmer’s operating logics is useful to approach farms adaptations capacity according to Dedieu et al. (2010). We determined three different operating logics, which follows diverse trajectories and motivations. With the study of long term operating logics inspired by Rigollot et al. (2019) and the study of farms trajectories inspired by Lamine et al. (2014), we are able to distinguish the three types’ adaptation capacities. The logic of “producing more with more standardized products” corresponding to the first type appears to be less resilient and flexible than the logic of “producing in adequacy with the available resources” corresponding to the third type. The second type seems to be located in between those two profiles and is focused on the diversification of the production and animal breeds, which brings adaptation capacities to their systems.

B. Advantages and limits of the method

With this research, we tried to characterize farmer’s strategies by considering the more elements as possible. Our survey method was partial and considering the short interviews, we were not able to

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understand all the components and flows of the farms. Yet, we were able to develop some important aspects to understand diversification strategies and farmers operating logics. We did not assess farms performances because of their inherent complexity and diversity. It does not seem relevant for us to use classical tools of assessment regarding the idiosyncrasy of these farms. Instead, we used a combination of different existent method and approach to create our framework. This framework allows us to make a first characterization of MLS in Languedoc and to build MLS models. Those models can be useful to understand the evolution and the possible expansion of this type of system. Creating an analysis framework is challenging regarding the multiple components and scales we considered around the farm: from the farm enterprises to the global management; from the territory embeddedness to sustainability aspects. This framework does not consider specific characteristic for each farm but aim to be transversal to understand dynamics that are more global.

Individual analysis formed the basis of the transversal analysis. With this first characterization, we were able to determine farms characteristics and to select the most relevant indicators. We did not take into account some indicators such as animal combination, animal products, crops rotation and renewal rate. Those information were too variable regarding the farms and some farmers didn’t have those type of information. We chose not considering those indicators to focus on others more selective and appropriate ones.

The transversal analysis allows us to establish a typology of three MLS models regarding their history, structure, practices and trajectories. This typology is a useful tool to understand the possible evolution and perspectives for MLS. The first limits of this typology is the small size of our sample. In fact, mixed livestock farms are quite unusual and rare in Languedoc Roussillon, especially in organic agriculture. It would be interesting to test this typology with others farms from other territories. This typology is a first tool in order to characterize mixed livestock farms and their perspectives, which have to be develop with other surveys.

Another aspect of our method is the large presence of qualitative indicators and the mix between quantitative and qualitative indicators. Our research method is based on semi-directed interviews, this allows the farmer to talk about topics and issues he is interested in. It gives crucial information for understanding the logic, the determinants and the choices of the farmers. In the same time, we wanted to have a minimum of quantitative dates to characterize the structure and the functioning of the farms. As a result, we obtained many quantitative and qualitative data and we selected the most relevant ones for our analysis and treated them with a mixed data statistical method.

The graphic representation with the “Grange” shows advantages and limits. This representation is useful to show the main advantages and issues of a territory shared by different actors and systems. It allows highlighting the diversity of services and impacts of a territory and confirming that one territory can be geared towards supply meanwhile another one is geared towards environmental and cultural issues. This graphic tool illustrate also more balanced systems. However, this tool has a limited heuristic scope according to the authors (Duru et al., 2017). The assessment method to determine the arrows size is quite subjective because we determined it by ourselves. Even if we created a table with a notation system, it is not a real sustainability assessment method. Once the “Grange” is created, it is interesting to confront it with the concerned actors. In our case, we discuss with three farmers during the workshop and they were in accordance with our conclusion about their systems. It would have be interesting to show them those “Grange” but they were not created yet.

We organized the participative framework during a high peak workload for the farmers and it prevented us to present results here. It was an interesting exercise but it does not give sufficient information to discuss about it. Still, the farmers present during the framework approved our models and conclusions.

35 C. Discussion of the results

All our results are based on farmer’s discourses during the interviews. The information given by the farmers were sometimes approximate and sometimes based on declarations documents. It brings few uncertainties to the results but it is the more efficient way to obtain a large amount of information about the farms and the practices. The individual indicators and the trajectories have been built regarding those discourses. We obtained 24 indicators and one trajectory per farm. With those results, we are able to understand the farm history, structure and functioning. The trajectories are very useful to understand the key elements of the farms with a qualitative approach. With those graphic representations, we have the main components and history for each farm. It helped us to determine the models by analysing each farm trajectory.

The three models obtained through the FAMD method can be discussed. The statistical analysis method is relevant regarding our mixed data. Thus, considering the large amount of indicators and their differences (from the lands repartition to the enterprises complementarities) the real statistical value can be contested. We decided to keep this method because we use it as a tool for discussion. The types are an illustration of farmer’s strategies and trajectories and they are flexible. For example, one farm can below to the third type but be close to the second type. It means it strategy tends to look like the second type even if it belongs mainly to the third type strategy. Each farm shows specific trajectories and strategies even in each model. The models are useful to draw general tendencies followed by the mixed livestock farms, not to describe each farm perfectly. We found that the models follow three different economic and development strategies. One model is more focused on the high valorisation of their products; another one on the rationalization of it production and the last one is focused on the diversification in order to stay viable. Those three strategies results from the farms history, structure, and environment and from the farmer personality.

The “Grange” allows us to illustrate the three strategic types with their services and impacts for the territory. It gives us interesting information about their contribution to the territory dynamic. For example, the second type has a balanced contribution between the main services and impacts meanwhile the two others are less balanced. The two other types do not contribute at the same level for their territory. We can imagine that these three models are coexisting in the same territory without too much competition regarding this high contrast. With the actual agricultural situation, we can make supposition about the future of these models and their contribution to the agroecological transition.

D. Perspective for MLS

We built three different MLS models with their own operating logics, trajectories and adaptations capacities. This modelling allows to distinguish different form of farm management with more generic and precise indicators than usual ones (organic/non organic for example). This distinction is outside the traditional agronomic method, the same way MLS are outside the traditional farming models. The characterization of MLS has been forgot by traditional methods because they tend to identify the most dominant systems at a territory scale (Dumont et al., 2017). Characterizing MLS means characterizing innovative systems in their relation with the territory, their mode of production and their practices. Therond et al. (2017) built a conceptual framework allowing representing different agricultural models regarding the inputs’ nature and source and their globalized or territory embeddedness.

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Figure 17: conceptual framework representing six agricultural models according to Therond et al. (2017)

With this framework, we are able to situate our own models. The third type seems to correspond to the “integrated food-energy systems” meanwhile the second one seems to correspond to the “biological input-based food system in circular economy”. The first type is more widespread, it starts from “chemical inputs based food system in globalised commodity-based food systems” to “biodiversity based FS in globalised commodity based food systems”. This graphic representation is useful to represent the coexistence between agriculture models and their possible evolution.

With this framework, we are able to represent the coexistence between our three MLS models and to imagine their possible transition from a model to another one. Regarding its own context, each model is able to move towards another one by mobilising levers such as circular economy, the autonomy quest, alternative mode of commercialisation or labels. The wide majority of the mixed livestock farms seems to mobilise those levers because of the high environmental and economic pressure on their systems. This specific context explains why those systems have developed innovative and agroecological practices. We can consider MLS as “niches”, they do not correspond to the main socio- technical regime. The multi-levels perspective proposed by Geels et al. (2004) consider the “niches” as incubators for a new way of producing. The “niches” studying, promotion and diffusion is useful to facilitate the dominant regime transition. As niches, MLS question the dominant livestock system which tend to be standardized and specialised. In the same time, those models seem difficult to generalize considering their specificities and the work hardness. To some extent, we can consider that MLS contribute to the agroecological transition by adopting innovative practices (from the production to the sales management), by contributing to the territory dynamic and by developing adaptation capacities linked with their environment.

37 E. Conclusion

First, we characterize mixed livestock farms through their structures, environment and functioning. It reveals that the surveyed farms were unique and have different constraints and advantages. The context of installation, the age, the environment, the animals combinations and many others indicators helped us to build a set of 24 descriptive indicators. We completed this table with the classification of the practices and the trajectories analysis. We can notice the strong link between the farmer’s motivation, his practices and his global functioning. The classification of practices revealed that there is a lot of variability regarding those practices and that mixed livestock farms tend to adopt agroecological or autonomous practices. The trajectories analysis shows the stability and the logic of action of each farmer. It helped us to make a link with adaptation capacities and to draw first conclusion about farms resilience, flexibility and vulnerability. For example, the farms with unstable practices and breaks in their trajectories seem more vulnerable than farms well settled with stable practices. This first step represents the individual analysis and it helped us for the transversal analysis.

With the transversal analysis, we were able to distinguish three models corresponding to: “maintaining in a sector crisis structure”, “optimisation after a hyper diversification” and “high valorisation in a constrained structure”. Those three models correspond to three different operating logics induced by their specific environment, structure and history. We assessed those three types with the “La Grange” method, which allows us to distinguish their territorial contribution. We found that each model contribute to the territory dynamic at different levels and scales. For example, the first type contribute more to the supply than the two others meanwhile the third one contribute more to the environmental issues than the two others. This territory assessment linked with our typology highlight the coexistence of different mixed livestock models in the Languedoc Roussillon territory.

If we compare our three models with the six agricultural models described by Therond et al. (2017), we found that each model is located at different position in the graphic representation. This confirm the coexistence between our models but it also stresses out the different form of transition each model can follow.

This research gives interesting tools to characterize and to model mixed livestock systems. We can make assumption about the MLS contribution for the agroecological transition considering them as niches in the dominant system. However, their high level of specificities and the work hardness described by the farmers can prevent those types of systems generalization. Considering the many issues linked to livestock systems, we suggest enhancing studies and researches about those systems and about others innovative systems. There is a need for innovation in agriculture according to Meynard et al. (2016) and it is possible through an innovative design process for radical innovations; the development of innovation “niches”; the sharing of expectations and knowledge to design together innovations. This research is a first step in the characterization and the redesign of livestock systems innovations and need to be deepened.

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